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February 6, 2017

Nexar Hires Professor Trevor Darrell as Chief Scientist

Professor in Residence Trevor Darrell has been hired as Chief Scientist at Nexar, the world's first over-the-top vehicle-to-vehicle (V2V) network that turns smartphones into Artificial Intelligence Dashcams. In parallel to his work in EECS, Darrell will lead research in the area of machine vision deep learning and vehicle path prediction, including leveraging the company's pool of rare large-scale driving data sets that contain video and telemetry of a variety of real-world driving environments to develop automotive applications.

When Will the Robots Rebel?

Associate Prof. Pieter Abbeel and the Robot Learning Lab are profiled in a comprehensive article for Datamation titled "Artificial Intelligence: When Will the Robots Rebel?" The article covers the foundational tools of AI, like machine learning, and delves into subjects like the human desire to replicate itself, the singularity, and the possibility of robot rebellion. It also looks at the ways AI currently impacts our lives and how it might change our future.

Prof. Ruzena Bajcsy, Assistant Prof. Anca Dragan, Prof. Ken Goldberg, and Dean Shankar Sastry are members of a Berkeley team participating in a new $253 million national consortium, the Advanced Robotics Manufacturing (ARM) Innovation Hub, led by the Department of Defense. The ARM consortium, which has academic and industrial partners in 31 states, is organizing domestic capabilities in robotics technology to amplify U.S. manufacturing. According to an article in Berkeley Engineering titled "Berkeley a regional center in new robotics manufacturing consortium," the Berkeley team is focussing on hybrid robotics, co-robotics, and assessing the environmental and resource issues associated with robotics manufacturing technology.

The search is on for interim dean of new Division of Data Science

Although it is too early to know the candidates, interim Executive Vice Chancellor and Provost Carol Christ has announced that a member of faculty will be appointed interim dean of the new Division of Data Science at UC Berkeley. Cathryn Carson, co-chair of the faculty advisory board, said the appointment of an interim dean is an important initial step in advancing the research and education of data science on campus. CS Prof. David Culler said UC Berkeley has already been developing the foundations of the new field, which lies at the intersection of computer science and statistics. Culler said the purpose of the new division is not only to distinguish the field with importance but also to integrate data science with all other divisions in the school. He added that the faculty advisory board hopes to include the division in the College of Letters and Sciences as well as the College of Engineering and that the position will give data science “a seat at the table” when deans are discussing on-campus issues.

Algorithm probes how AIs reason

Quartz explores an algorithm devised by CS Prof. Trevor Darrell, L&S CS undergraduate student Dong Huk Park, CS grad student Lisa Anne Hendricks, and postdoc Marcus Rohrbach, along with researchers in the Max Planck Institute for Informatics, in an article titled "We don’t understand how AI make most decisions, so now algorithms are explaining themselves." Engineers have developed deep learning systems that ‘work’ without necessarily knowing why they work or being able to show the logic behind a system’s decision. The algorithm uses a “pointing and justification” system, to point to the data used to make a decision and justify why it was used that way.

Prof. Clark Nguyen has been selected to receive the 2017 Robert Bosch Micro and Nano Electro Mechanical Systems Award. This award was established by the IEEE Electron Devices Society in 2014 to recognize and honor advances in the invention, design, and/or fabrication of micro or nano- electromechanical systems and/or devices. The contributions honored by this award are innovative and useful for practical applications. Prof. Nguyen is being honored for pioneering research on high-frequency MEMS vibrating systems and for extraordinary efforts in support of MEMS in industry, government, and teaching.

New ultrasonic sensors can improve security of fingerprint recognition on smartphones

EE Prof. Bernhard Boser is profiled in an article in the Cal Aggie titled "Fingerprint recognition on smartphones unsafe and hackable" in which he discusses a new ultrasonic imaging process developed at UC Berkeley and UC Davis to more securely protect personal information than current finger recognition technologies. This new technology, which combines an ultrasonic sensor in air and an ultrasonic sensor in tissue, captures a fingerprint in 3D to uniquely identify a person. It images both the ridges and valleys of a fingerprint surface as well as the subsurface structure of the skin, distinguishing between layers of tissue by analyzing the densities of live and dead skin cells. "This imaging process can look at the surface of fingerprints and inside the finger,” Boser said. “There are more patterns inside the finger that can’t be put onto glass screen of a phone.”

A Computational Imaging research proposal submitted by EE Associate Prof. Laura Waller, EE Associate Prof. Michael Lustig, CS Assistant Prof. Ren Ng, CS Assistant Prof. Jonathan Ragan-Kelley, and CS Associate Prof. Benjamin Rechts has been accepted as part of a set of cross-disciplinary activities planned for development by Berkeley Research. Berkeley Research ran eight faculty forums on a wide range of topics and received 30 proposals which were reviewed by a faculty panel and discussed with the Deans. The selected projects "hold great promise for Berkeley to be at the forefront of developing a positive vision for the future."

Ali Javey's team's Wearable Sweat Bio-sensor

Prof. Ali Javey and his team's presentation at the 2016 International Electron Devices Meeting (IEDM) is profiled in an EE Times article titled "Sweating Big Human-Body Data Challenge." This year, IEDM papers explored a number of technologies to make flexible and printable electronics, and Prof. Javey's team's paper stood out. Unlike conventional wearable devices, the team has zeroed in on the idea of attaching sweat biosensors — like a patch — on the body to collect sweat as it appears, for “real-time perspiration analysis.”